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Job Title : Data Quality Engineer (Data QE) We are seeking a skilled and experienced Data Quality Engineer (Data QE) to join our team. The ideal candidate will have a strong background in Quality Engineering, ETL and database testing, and hands-on expertise with Python, PySpark, SQL, and Databricks. You will be responsible for designing and executing tests to ensure the quality and reliability of data pipelines and analytics platforms. Key Responsibilities : Design and implement end-to-end test strategies for data pipelines and ETL processes. Conduct thorough ETL and database testing to ensure data accuracy, completeness, and consistency. Develop automation frameworks and scripts using Python and PySpark. Perform data validation and integrity checks using advanced SQL queries. Work with big data platforms such as Databricks for testing and validation. Collaborate closely with data engineers, analysts, and product teams to understand data requirements. Identify data quality issues, troubleshoot, and work with stakeholders to resolve them. Document test cases, results, and provide regular status updates. Mandatory Skills & Experience : 6+ years of experience in Quality Engineering and QE processes. 2-3 years of hands-on experience in ETL testing and database testing. 2-3 years of experience with Python and PySpark for data testing and automation. 2-3 years of experience in writing complex SQL queries for data validation. Experience working with Databricks or similar big data platforms. Preferred Qualifications : Experience with cloud data platforms (e.g., AWS, Azure, GCP). Familiarity with CI/CD pipelines and test automation tools. Knowledge of data governance and data quality frameworks. Education : Bachelors or Masters degree in Computer Science, Information Systems, or a related field. .
Here's how to pick the right one and stand out in your application.
144.883Jobs
31.687IN
81%EN
That number is real. WorkMundi's database shows 144,883 open engineer roles across the world. India has the most with 31,687 jobs, followed by the United States with 30,084. If you just finished reading one job ad and felt paralyzed by choice, you're not alone—but this scale is actually an advantage. It means you can afford to be selective.
Start by geography and language. The majority of engineer ads—117,837 of them—have the job posting text written in English. Use that as one filter, but remember: the ad text language tells you nothing about whether the role actually requires you to speak English day-to-day. Read the job description carefully. Then check which countries have the volume you're targeting. Singapore, Poland, and Australia round out the top five after India and the US.
Next, learn who's hiring. Accenture has posted 2,801 engineer roles. andurilindustries, speechify, and jobgether are also actively recruiting. If you're applying to one of these names, research their hiring patterns and interview style before you apply. That homework pays off.
When you interview, expect the question every engineer hears: 'Tell me about a time you had to debug a problem that wasn't in your job description.' Have a specific story ready—not a general one. Name the tools, the deadline pressure, and what you learned. Hiring managers listen for whether you see problem-solving as part of the role itself, not a favour.